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Database normalization is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model .
"Don't repeat yourself" (DRY), also known as "duplication is evil", is a principle of software development aimed at reducing repetition of information which is likely to change, replacing it with abstractions that are less likely to change, or using data normalization which avoids redundancy in the first place.
This was the first time the notion of a relational database was published. All work after this, including the Boyce–Codd normal form method was based on this relational model. The Boyce–Codd normal form was first described by Ian Heath in 1971, and has also been called Heath normal form by Chris Date .
A database relation (e.g. a database table) is said to meet third normal form standards if all the attributes (e.g. database columns) are functionally dependent on solely a key, except the case of functional dependency whose right hand side is a prime attribute (an attribute which is strictly included into some key).
In a hierarchical database, a record can contain sets of child records ― known as repeating groups or table-valued attributes.If such a data model is represented as relations, a repeating group would be an attribute where the value is itself a relation.
Denormalization is a strategy used on a previously-normalized database to increase performance. In computing, denormalization is the process of trying to improve the read performance of a database, at the expense of losing some write performance, by adding redundant copies of data or by grouping data.
Record locking is the technique of preventing simultaneous access to data in a database, to prevent inconsistent results.. The classic example is demonstrated by two bank clerks attempting to update the same bank account for two different transactions.
In computer science, in the field of databases, read–write conflict, also known as unrepeatable reads, is a computational anomaly associated with interleaved execution of transactions. Specifically, a read–write conflict occurs when a "transaction requests to read an entity for which an unclosed transaction has already made a write request."